Currently, the `object.__setattr__` and `type.__setattr__` methods raise an `AttributeError` during attribute *update* on an instance if its type has an attribute which is a *data* descriptor without a `__set__` method. Likewise, the `object.__delattr__` and `type.__delattr__` methods raise an `AttributeError` during attribute *deletion* on an instance if its type has an attribute which is a *data* descriptor without a `__delete__` method.

This should not be the case. When update/deletion is impossible through a data descriptor found on the type, update/deletion should carry its process on the instance, like when there is no data descriptor found on the type. And this is what the `object.__getattribute__` and `type.__getattribute__` methods already do: they do *not* raise an `AttributeError` during attribute *lookup* on an instance if its type has an attribute which is a *data* descriptor without a `__get__` method. See [the discussion on Python Discuss](https://discuss.python.org/t/why-do-setattr-and-delattr-raise-an-attributeerror-in-this-case/7836?u=maggyero).

Here is a simple program illustrating the differences between attribute lookup by `object.__getattribute__` on the one hand (`AttributeError` is not raised), and attribute update by `object.__setattr__` and attribute deletion by `object.__delattr__` on the other hand (`AttributeError` is raised):

```python
class DataDescriptor1:  # missing __get__
    def __set__(self, instance, value): pass
    def __delete__(self, instance): pass

class DataDescriptor2:  # missing __set__
    def __get__(self, instance, owner=None): pass
    def __delete__(self, instance): pass

class DataDescriptor3:  # missing __delete__
    def __get__(self, instance, owner=None): pass
    def __set__(self, instance, value): pass

class A:
    x = DataDescriptor1()
    y = DataDescriptor2()
    z = DataDescriptor3()

a = A()
vars(a).update({'x': 'foo', 'y': 'bar', 'z': 'baz'})

a.x
# actual: returns 'foo'
# expected: returns 'foo'

a.y = 'qux'
# actual: raises AttributeError: __set__
# expected: vars(a)['y'] == 'qux'

del a.z
# actual: raises AttributeError: __delete__
# expected: 'z' not in vars(a)
```

Here is another simple program illustrating the differences between attribute lookup by `type.__getattribute__` on the one hand (`AttributeError` is not raised), and attribute update by `type.__setattr__` and attribute deletion by `type.__delattr__` on the other hand (`AttributeError` is raised):

```python
class DataDescriptor1:  # missing __get__
    def __set__(self, instance, value): pass
    def __delete__(self, instance): pass

class DataDescriptor2:  # missing __set__
    def __get__(self, instance, owner=None): pass
    def __delete__(self, instance): pass

class DataDescriptor3:  # missing __delete__
    def __get__(self, instance, owner=None): pass
    def __set__(self, instance, value): pass

class M(type):
    x = DataDescriptor1()
    y = DataDescriptor2()
    z = DataDescriptor3()

class A(metaclass=M):
    x = 'foo'
    y = 'bar'
    z = 'baz'

A.x
# actual: returns 'foo'
# expected: returns 'foo'

A.y = 'qux'
# actual: raises AttributeError: __set__
# expected: vars(A)['y'] == 'qux'

del A.z
# actual: raises AttributeError: __delete__
# expected: 'z' not in vars(A)
```

I'm going to decline this one.  

* It is arguable whether or not this behavior should have been designed in originally.  However, changing it now is risky (as noted by Brett and Ethan).

* Personally, I disagree with the notion of allowing a partial pass through.  That seems hazardous and error-prone to me.  It is easier to reason about data descriptors being all or nothing.  I like that AttributeError is raised while still allowing me to add the missing methods if I want to explicitly define some other behavior. 

* This has been open for 9 months and no one else stepped forward to champion it.

* For two decades, no one has complained that the current behavior got in the way of what they were trying to do.  That provides some evidence that there isn't a real world problem to be solved.